Quicklinks

Introduction to Data Management

Managing your data can be an effective strategy for ensuring that your
data will be usable preserved, maintained, and accessible throughout the
life cycle of a research project and for future generations of scientific
research.

Moreover, federal funding agencies are now requiring data management
plans as part of grant proposal packages.

What is Data?

(i) Research data is defined as the recorded factual material commonly accepted
in the scientific community as necessary to validate research findings, but not
any of the following: preliminary analyses, drafts of scientific papers, plans
for future research, peer reviews, or communications with colleagues. This "recorded"
material excludes physical objects (e.g., laboratory samples). Research data also do
not include:

(A) Trade secrets, commercial information, materials necessary to be held confidential
by a researcher until they are published, or similar information which is protected under
law; and

(B) Personnel and medical information and similar information the disclosure of which
would constitute a clearly unwarranted invasion of personal privacy, such as information
that could be used to identify a particular person in a research study.

Funding Agency Requirements

The sharing of research findings has always been critical to the development
of science. Whether through society publications, corporate publishing, or
open access forums, scientific progress is dependent upon the sharing of data
collected through:

observation (e.g. sensor or survey data),

experimentation (e.g. gene sequences, chromatograms)

simulation (e.g. climate or economic models), and

derivation/compilation (e.g. text and data mining, 3D models).

In order to foster scientific progress and promote the expansion and
diverity of user communicatinos, the National Institutes of Health and the
National Science Foundation have issued data sharing mandates for projects
funded by their agencies. This means that researchers receiving funds from
these agencies are subject to the requirements of these mandates.

Example Data Management Plans

The following list of Data Management Plan examples are available for variety
of research domains. Use the following examples as a guide to writing your own:

Data Management Tools

Preparing your data for effective management throughout the data lifecycle and adhering
to agency mandates does not have to be a time consuming task. The following tools
will help you create a well-organized Data Management Plan with ease:

DMPTool provides uidance and resources for your Data Management Plan
The DMP tool is the product of a joint effort by several Major American Research
Institutions. The goal is to provide a "flexible, online tool to help researchers create
data management plans." With the DMPTool, rsearchers can:

The Digital Curation Center Data Management and Sharing Plan Website
is the "leading hub of expertise in curating digital research" in the United Kingdom. Much
like the DMPTool, the DCC's DMP tool is a flexible web-based tool that allows rsearchers to
create personalized data management plans, and includes many of the same features as DMPTool.

A recommended list of elements to be included in a Data Management Plan

The DataONE Data Management Plan Outline
is a quick reference guide for outlining a Data Management Plan, and provides a generic
example of how each section fo the plan may look once completed.

Data Sharing

Your data is a source of potential value to resarchers and society at large, and sharing
it helps to put its potential value to use. In order to maximize the value of your data,
it is imperative to inform others how they can use it, while protecting your rights as the
creator.

The most effective way of informing others of how they can use your data is by applying
a license to its use.

If you want to find a license that is right for youd ata or learn more about licensing
data in general, please refer to the following resources: